Image Retrieval Based on Block Color Volume Kernel Feature and MLBP

In this paper, a method of image retrieval based on block color volume kernel feature and modified Local Binary Pattern (MLBP) is proposed. First the image is divided into blocks and nine overlapping sub block histogram to extract color volume, and low dimensional color feature mapped into high dimensional kernel space of image before filtering using the Gauss kernel function, and then extract texture features of the returned image using MLBP operator, finally the feature similarity measure. The experimental results show that, compared with the image with color volume histogram, block color histogram and LBP operator for feature retrieval method, The algorithm can improve the accuracy of retrieval results, improve the sorting value of related images, and has a good anti noise performance.